摘要
为了优化电子元件表面缺陷检测效果,提升缺陷检测率,实现自动、快速、准确的检测目标,引入计算机视觉,提出了一种全新的电子元件表面缺陷检测算法。首先,拍摄电子元件表面图像,对图像进行滤波处理,消除原始图像中多余的噪声;其次,基于阈值分割原理,将电子元件图像划分成若干个区域,从各个区域中提取与元件表面缺陷相关的特征,初步检测电子元件表面缺陷;在此基础上,基于计算机视觉技术,设计电子元件表面缺陷检测算法,进一步精确检测元件表面是否存在缺陷。实验结果表明,提出的检测算法应用后,6种不同类型的电子元件表面缺陷检测率均较高,检测能力更强,准确性和可靠性优势显著。
In order to optimize the surface defect detection effect of electronic components,improve the defect detection rate,and achieve automatic,fast,and accurate detection goals,a new electronic component surface defect detection algorithm is proposed by introducing computer vision.Firstly,take surface images of electronic components and filter the images to eliminate excess noise in the original image·Secondly,based on the principle of threshold segmentation,the electronic component image is divided into several regions,and features related to surface defects of the component are extracted from each region to preliminarily detect surface defects of the electronic component;On this basis,based on computer vision technology,a surface defect detection algorithm for electronic components is designed to further accurately detect whether there are defects on the surface of the components.The experimental results show that after the application of the proposed detection algorithm,the surface defect detection rate of six different types of electronic components is higher,the detection ability is stronger,and the accuracy and reliability advantages are significant.
作者
任学龙
Ren Xueong(Lima Optoelectronic Technology(Beijing)Co.,Ltd.,Beijing,China)
出处
《科学技术创新》
2024年第6期116-119,共4页
Scientific and Technological Innovation
关键词
计算机视觉
电子
元件
表面
缺陷
检测
算法
computer vision
electronics
components
surface
defects
detection
algorithm